Ionosphere weighted global positioning system carrier phase ambiguity resolution

Integer Ambiguity constraint is essential in precise GPS positioning. The performance and reliability of the ambiguity resolution process are being hampered by the current culmination (Y2000) of the eleven-year solar cycle. The traditional approach to mitigate the high ionospheric effect has been either to reduce the inter-station separation or to form ionosphere-free observables. Neither is satisfactory: the first restricts the operating range, and the second no longer possesses the ”integerness” of the ambiguities. A third generalized approach is introduced herein, whereby the zero ionosphere weight constraint, or pseudo-observables, with an appropriate weight is added to the Kalman Filter algorithm. The weight can be tightly fixed yielding the model equivalence of an independent L1/L2 dual-band model. At the other extreme, an infinite floated weight gives the equivalence of an ionosphere-free model, yet perserves the ambiguity integerness. A stochastically tuned, or weighted, model provides a compromise between the two extremes. The reliability of ambiguity estimates relies on many factors, including an accurate functional model, a realistic stochastic model, and a subsequent efficient integer search algorithm. These are examined closely in this research. Two days of selected Swedish GPS Network data sets from ionospherically active (up to 15 ppm) and moderate (up to 4 ppm) days, forming a maximum baseline length of 400 km, have been analyzed. All three ionosphere weight models yielded a 90% range of correct widelane ambiguities within three minutes, regardless of interiii